Modeling gene-regulatory networks to describe cell fate transitions and predict master regulators
Artikel i vetenskaplig tidskrift, 2018
Complex organisms originate from and are maintained by the information encoded in the genome. A major challenge of systems biology is to develop algorithms that describe the dynamic regulation of genome functions from large omics datasets. Here, we describe TETRAMER, which reconstructs gene-regulatory networks from temporal transcriptome data during cell fate transitions to predict “master” regulators by simulating cascades of temporal transcription-regulatory events.
Författare
Pierre-Etienne Cholley
Chalmers, Biologi och bioteknik, Systembiologi
Université de Strasbourg
CSBI
Julien Moehlin
Université de Strasbourg
Alexia Rohmer
Université de Strasbourg
Vincent Zilliox
Université de Strasbourg
Samuel Nicaise
Université de Strasbourg
Hinrich Gronemeyer
Université de Strasbourg
Marco Antonio Mendoza-Parra
Genomique Metabolique
Université de Strasbourg
npj Systems Biology and Applications
2056-7189 (eISSN)
Vol. 4 1 29Ämneskategorier
Utvecklingsbiologi
Bioinformatik (beräkningsbiologi)
Bioinformatik och systembiologi
DOI
10.1038/s41540-018-0066-z